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SQL JOIN 连接


SQL 连接(JOIN) 子句用于将数据库中两个或者两个以上表中的记录组合起来。连接通过共有值将不同表中的字段组合在一起。

我们来看看"Orders"表中的选择:

OrderIDCustomerIDOrderDate
1030821996-09-18
10309371996-09-19
10310771996-09-20

然后,查看"Customers"表中的选择:

CustomerIDCustomerNameContactNameCountry
1Alfreds FutterkisteMaria AndersGermany
2Ana Trujillo Emparedados y heladosAna TrujilloMexico
3Antonio Moreno TaqueríaAntonio MorenoMexico

请注意,"Orders"表中的"客户ID"列是指"CustomerID"表中的"客户ID"。上面两个表格之间的关系是"CustomerID"列。

然后,我们可以创建下面的SQL语句(包含一个INNER JOIN),它选择两个表中具有匹配值的记录:

** 代码示例:**

sql
SELECT Orders.OrderID, Customers.CustomerName, Orders.OrderDate
FROM Orders
INNER JOIN Customers ON Orders.CustomerID=Customers.CustomerID;

它会产生这样的东西:

OrderIDCustomerNameOrderDate
10308Ana Trujillo Emparedados y helados9/18/1996
10365Antonio Moreno Taquería11/27/1996
10383Around the Horn12/16/1996
10355Around the Horn11/15/1996
10278Berglunds snabbköp8/12/1996

考虑下面两个表,(a)CUSTOMERS 表:

sql
    +----+----------+-----+-----------+----------+
    | ID | NAME     | AGE | ADDRESS   | SALARY |
    +----+----------+-----+-----------+----------+
    | 1 | Ramesh   | 32 | Ahmedabad | 2000.00 |
    | 2 | Khilan   | 25 | Delhi     | 1500.00 |
    | 3 | kaushik  | 23 | Kota      | 2000.00 |
    | 4 | Chaitali | 25 | Mumbai    | 6500.00 |
    | 5 | Hardik   | 27 | Bhopal    | 8500.00 |
    | 6 | Komal    | 22 | MP        | 4500.00 |
    | 7 | Muffy    | 24 | Indore    | 10000.00 |
    +----+----------+-----+-----------+----------+

(b)另一个表是 ORDERS 表:

sql
    +-----+---------------------+-------------+--------+
    |OID | DATE                | CUSTOMER_ID | AMOUNT | +-----+---------------------+-------------+--------+ | 102 | 2009-10-08 00:00:00 |           3 | 3000 |
    | 100 | 2009-10-08 00:00:00 | 3 |   1500 | | 101 | 2009-11-20 00:00:00 |           2 | 1560 |
    | 103 | 2008-05-20 00:00:00 | 4 |   2060 | +-----+---------------------+-------------+--------+

现在,让我们用 SELECT 语句将这个两张表连接(JOIN)在一起:

sql
    SQL> SELECT ID, NAME, AGE, AMOUNT
            FROM CUSTOMERS, ORDERS
            WHERE  CUSTOMERS.ID = ORDERS.CUSTOMER_ID;

上述语句的运行结果如下所示:

sql
    +----+----------+-----+--------+
    | ID | NAME     | AGE | AMOUNT | +----+----------+-----+--------+ |  3 | kaushik |  23 | 3000 |
    | 3 | kaushik  | 23 |   1500 | |  2 | Khilan |  25 | 1560 |
    | 4 | Chaitali | 25 |   2060 | +----+----------+-----+--------+

不同类型的SQL联接


SQL 中有多种不同的连接:

  • 内连接(INNER JOIN):当两个表中都存在匹配时,才返回行。
  • 左连接(LEFT JOIN):返回左表中的所有行,即使右表中没有匹配的行。
  • 右连接(RIGHT JOIN):返回右表中的所有行,即使左表中没有匹配的行。
  • 全连接(FULL JOIN):只要某一个表存在匹配,就返回行。
  • 笛卡尔连接(CARTESIAN JOIN):返回两个或者更多的表中记录集的笛卡尔积。

内连接

最常用也最重要的连接形式是内连接,有时候也被称作"EQUIJOIN"(等值连接)。

内连接根据连接谓词来组合两个表中的字段,以创建一个新的结果表。SQL 查询会比较逐个比较表 1 和表 2 中的每一条记录,来寻找满足连接谓词的所有记录对。当连接谓词得以满足时,所有满足条件的记录对的字段将会结合在一起构成结果表。

语法:

** 内连接**的基本语法如下所示:

sql
SELECT table1.column1, table2.column2...
FROM table1
INNER JOIN table2
ON table1.common_field = table2.common_field;

示例:

考虑如下两个表格,(a)CUSTOMERS 表:

sql
+----+----------+-----+-----------+----------+
| ID | NAME     | AGE | ADDRESS   | SALARY |
+----+----------+-----+-----------+----------+
| 1 | Ramesh   | 32 | Ahmedabad | 2000.00 |
| 2 | Khilan   | 25 | Delhi     | 1500.00 |
| 3 | kaushik  | 23 | Kota      | 2000.00 |
| 4 | Chaitali | 25 | Mumbai    | 6500.00 |
| 5 | Hardik   | 27 | Bhopal    | 8500.00 |
| 6 | Komal    | 22 | MP        | 4500.00 |
| 7 | Muffy    | 24 | Indore    | 10000.00 |
+----+----------+-----+-----------+----------+

(b)ORDERS 表:

sql
+-----+---------------------+-------------+--------+
| OID | DATE                | ID | AMOUNT | +-----+---------------------+-------------+--------+ | 102 | 2009-10-08 00:00:00 |           3 | 3000 |
| 100 | 2009-10-08 00:00:00 | 3 |   1500 | | 101 | 2009-11-20 00:00:00 |           2 | 1560 |
| 103 | 2008-05-20 00:00:00 | 4 |   2060 | +-----+---------------------+-------------+--------+

现在,让我们用内连接将这两个表连接在一起:

sql
SQL> SELECT  ID, NAME, AMOUNT, DATE
     FROM CUSTOMERS
     INNER JOIN ORDERS
     ON CUSTOMERS.ID = ORDERS.CUSTOMER_ID;

上述语句将会产生如下结果:

sql
+----+----------+--------+---------------------+
| ID | NAME     | AMOUNT | DATE                | +----+----------+--------+---------------------+ |  3 | kaushik |   3000 | 2009-10-08 00:00:00 |
| 3 | kaushik  | 1500 | 2009-10-08 00:00:00 | |  2 | Khilan |   1560 | 2009-11-20 00:00:00 |
| 4 | Chaitali | 2060 | 2008-05-20 00:00:00 | +----+----------+--------+---------------------+

左连接

** 左链接**返回左表中的所有记录,即使右表中没有任何满足匹配条件的记录。这意味着,如果 ON 子句在右表中匹配到了 0 条记录,该连接仍然会返回至少一条记录,不过返回的记录中所有来自右表的字段都为 NULL。

这就意味着,左连接会返回左表中的所有记录,加上右表中匹配到的记录,或者是 NULL (如果连接谓词无法匹配到任何记录的话)。

语法:

** 左连接**的基本语法如下所示:

sql
SELECT table1.column1, table2.column2...
FROM table1
LEFT JOIN table2
ON table1.common_field = table2.common_field;

这里,给出的条件可以是任何根据你的需要写出的条件。

示例:

考虑如下两个表格,(a)CUSTOMERS 表:

sql
+----+----------+-----+-----------+----------+
| ID | NAME     | AGE | ADDRESS   | SALARY |
+----+----------+-----+-----------+----------+
| 1 | Ramesh   | 32 | Ahmedabad | 2000.00 |
| 2 | Khilan   | 25 | Delhi     | 1500.00 |
| 3 | kaushik  | 23 | Kota      | 2000.00 |
| 4 | Chaitali | 25 | Mumbai    | 6500.00 |
| 5 | Hardik   | 27 | Bhopal    | 8500.00 |
| 6 | Komal    | 22 | MP        | 4500.00 |
| 7 | Muffy    | 24 | Indore    | 10000.00 |
+----+----------+-----+-----------+----------+

(b)ORDERS 表:

sql
+-----+---------------------+-------------+--------+
| OID | DATE                | ID | AMOUNT | +-----+---------------------+-------------+--------+ | 102 | 2009-10-08 00:00:00 |           3 | 3000 |
| 100 | 2009-10-08 00:00:00 | 3 |   1500 | | 101 | 2009-11-20 00:00:00 |           2 | 1560 |
| 103 | 2008-05-20 00:00:00 | 4 |   2060 | +-----+---------------------+-------------+--------+

现在,让我们用左连接将这两个表连接在一起:

sql
SQL> SELECT  ID, NAME, AMOUNT, DATE
     FROM CUSTOMERS
     LEFT JOIN ORDERS
     ON CUSTOMERS.ID = ORDERS.CUSTOMER_ID;

上述语句将会产生如下结果:

sql
+----+----------+--------+---------------------+
| ID | NAME     | AMOUNT | DATE                | +----+----------+--------+---------------------+ |  1 | Ramesh |   NULL | NULL |
| 2 | Khilan   | 1560 | 2009-11-20 00:00:00 | |  3 | kaushik |   3000 | 2009-10-08 00:00:00 |
| 3 | kaushik  | 1500 | 2009-10-08 00:00:00 | |  4 | Chaitali |   2060 | 2008-05-20 00:00:00 |
| 5 | Hardik   | NULL | NULL                | |  6 | Komal |   NULL | NULL |
| 7 | Muffy    | NULL | NULL                | +----+----------+--------+---------------------+

右连接

** 右链接**返回右表中的所有记录,即是左表中没有任何满足匹配条件的记录。这意味着,如果 ON 子句在左表中匹配到了 0 条记录,该连接仍然会返回至少一条记录,不过返回的记录中所有来自左表的字段都为 NULL。

这就意味着,右连接会返回右表中的所有记录,加上左表中匹配到的记录,或者是 NULL (如果连接谓词无法匹配到任何记录的话)。

语法:

** 右连接**的基本语法如下所示:

sql
SELECT table1.column1, table2.column2...
FROM table1
RIGHT JOIN table2
ON table1.common_field = table2.common_field;

这里,给出的条件可以是任何根据你的需要写出的条件。

示例:

考虑如下两个表格,(a)CUSTOMERS 表:

sql
+----+----------+-----+-----------+----------+
| ID | NAME     | AGE | ADDRESS   | SALARY |
+----+----------+-----+-----------+----------+
| 1 | Ramesh   | 32 | Ahmedabad | 2000.00 |
| 2 | Khilan   | 25 | Delhi     | 1500.00 |
| 3 | kaushik  | 23 | Kota      | 2000.00 |
| 4 | Chaitali | 25 | Mumbai    | 6500.00 |
| 5 | Hardik   | 27 | Bhopal    | 8500.00 |
| 6 | Komal    | 22 | MP        | 4500.00 |
| 7 | Muffy    | 24 | Indore    | 10000.00 |
+----+----------+-----+-----------+----------+

(b)ORDERS 表:

sql
+-----+---------------------+-------------+--------+
| OID | DATE                | ID | AMOUNT | +-----+---------------------+-------------+--------+ | 102 | 2009-10-08 00:00:00 |           3 | 3000 |
| 100 | 2009-10-08 00:00:00 | 3 |   1500 | | 101 | 2009-11-20 00:00:00 |           2 | 1560 |
| 103 | 2008-05-20 00:00:00 | 4 |   2060 | +-----+---------------------+-------------+--------+

现在,让我们用右连接将这两个表连接在一起:

sql
SQL> SELECT  ID, NAME, AMOUNT, DATE
     FROM CUSTOMERS
     RIGHT JOIN ORDERS
     ON CUSTOMERS.ID = ORDERS.CUSTOMER_ID;

上述语句将会产生如下结果:

sql
+------+----------+--------+---------------------+
| ID | NAME     | AMOUNT | DATE                | +------+----------+--------+---------------------+ |    3 | kaushik |   3000 | 2009-10-08 00:00:00 |
| 3 | kaushik  | 1500 | 2009-10-08 00:00:00 | |    2 | Khilan |   1560 | 2009-11-20 00:00:00 |
| 4 | Chaitali | 2060 | 2008-05-20 00:00:00 | +------+----------+--------+---------------------+

全连接

** 全连接**将左连接和右连接的结果组合在一起。

语法:

** 全连接**的基本语法如下所示:

sql
SELECT table1.column1, table2.column2...
FROM table1
FULL JOIN table2
ON table1.common_field = table2.common_field;

这里,给出的条件可以是任何根据你的需要写出的条件。

示例:

考虑如下两个表格,(a)CUSTOMERS 表:

sql
+----+----------+-----+-----------+----------+
| ID | NAME     | AGE | ADDRESS   | SALARY |
+----+----------+-----+-----------+----------+
| 1 | Ramesh   | 32 | Ahmedabad | 2000.00 |
| 2 | Khilan   | 25 | Delhi     | 1500.00 |
| 3 | kaushik  | 23 | Kota      | 2000.00 |
| 4 | Chaitali | 25 | Mumbai    | 6500.00 |
| 5 | Hardik   | 27 | Bhopal    | 8500.00 |
| 6 | Komal    | 22 | MP        | 4500.00 |
| 7 | Muffy    | 24 | Indore    | 10000.00 |
+----+----------+-----+-----------+----------+

(b)ORDERS 表:

sql
+-----+---------------------+-------------+--------+
| OID | DATE                | ID | AMOUNT | +-----+---------------------+-------------+--------+ | 102 | 2009-10-08 00:00:00 |           3 | 3000 |
| 100 | 2009-10-08 00:00:00 | 3 |   1500 | | 101 | 2009-11-20 00:00:00 |           2 | 1560 |
| 103 | 2008-05-20 00:00:00 | 4 |   2060 | +-----+---------------------+-------------+--------+

现在让我们用全连接将两个表连接在一起:

sql
SQL> SELECT  ID, NAME, AMOUNT, DATE
     FROM CUSTOMERS
     FULL JOIN ORDERS
     ON CUSTOMERS.ID = ORDERS.CUSTOMER_ID;

上述语句将会产生如下结果:

sql
+------+----------+--------+---------------------+
| ID | NAME     | AMOUNT | DATE                | +------+----------+--------+---------------------+ |    1 | Ramesh |   NULL | NULL |
| 2 | Khilan   | 1560 | 2009-11-20 00:00:00 | |    3 | kaushik |   3000 | 2009-10-08 00:00:00 |
| 3 | kaushik  | 1500 | 2009-10-08 00:00:00 | |    4 | Chaitali |   2060 | 2008-05-20 00:00:00 |
| 5 | Hardik   | NULL | NULL                | |    6 | Komal |   NULL | NULL |
| 7 | Muffy    | NULL | NULL                | |    3 | kaushik |   3000 | 2009-10-08 00:00:00 |
| 3 | kaushik  | 1500 | 2009-10-08 00:00:00 | |    2 | Khilan |   1560 | 2009-11-20 00:00:00 |
| 4 | Chaitali | 2060 | 2008-05-20 00:00:00 | +------+----------+--------+---------------------+

如果你所用的数据库不支持全连接,比如 MySQL,那么你可以使用 UNION ALL子句来将左连接和右连接结果组合在一起:

sql
SQL> SELECT  ID, NAME, AMOUNT, DATE
     FROM CUSTOMERS
     LEFT JOIN ORDERS
     ON CUSTOMERS.ID = ORDERS.CUSTOMER_ID
UNION ALL
     SELECT  ID, NAME, AMOUNT, DATE
     FROM CUSTOMERS
     RIGHT JOIN ORDERS
     ON CUSTOMERS.ID = ORDERS.CUSTOMER_ID

笛卡尔连接(交叉连接)

** 笛卡尔连接** 或者交叉连接返回两个或者更多的连接表中记录的笛卡尔乘积。也就是说,它相当于连接谓词总是为真或者缺少连接谓词的内连接。

语法:

** 笛卡尔连接** 或者说交叉连接的基本语法如下所示:

sql
SELECT table1.column1, table2.column2...
FROM  table1, table2 [, table3 ]

示例:

sql
考虑如下两个表格,(a)CUSTOMERS 表:

    +----+----------+-----+-----------+----------+
    | ID | NAME     | AGE | ADDRESS   | SALARY |
    +----+----------+-----+-----------+----------+
    | 1 | Ramesh   | 32 | Ahmedabad | 2000.00 |
    | 2 | Khilan   | 25 | Delhi     | 1500.00 |
    | 3 | kaushik  | 23 | Kota      | 2000.00 |
    | 4 | Chaitali | 25 | Mumbai    | 6500.00 |
    | 5 | Hardik   | 27 | Bhopal    | 8500.00 |
    | 6 | Komal    | 22 | MP        | 4500.00 |
    | 7 | Muffy    | 24 | Indore    | 10000.00 |
    +----+----------+-----+-----------+----------+

(b)ORDERS 表:

    +-----+---------------------+-------------+--------+
    | OID | DATE                | ID | AMOUNT | +-----+---------------------+-------------+--------+ | 102 | 2009-10-08 00:00:00 |           3 | 3000 |
    | 100 | 2009-10-08 00:00:00 | 3 |   1500 | | 101 | 2009-11-20 00:00:00 |           2 | 1560 |
    | 103 | 2008-05-20 00:00:00 | 4 |   2060 | +-----+---------------------+-------------+--------+

现在,让我用内连接将这两个表连接在一起:

sql
SQL> SELECT  ID, NAME, AMOUNT, DATE
     FROM CUSTOMERS, ORDERS;

上述语句将会产生如下结果:

sql
+----+----------+--------+---------------------+
| ID | NAME     | AMOUNT | DATE                | +----+----------+--------+---------------------+ |  1 | Ramesh |   3000 | 2009-10-08 00:00:00 |
| 1 | Ramesh   | 1500 | 2009-10-08 00:00:00 | |  1 | Ramesh |   1560 | 2009-11-20 00:00:00 |
| 1 | Ramesh   | 2060 | 2008-05-20 00:00:00 | |  2 | Khilan |   3000 | 2009-10-08 00:00:00 |
| 2 | Khilan   | 1500 | 2009-10-08 00:00:00 | |  2 | Khilan |   1560 | 2009-11-20 00:00:00 |
| 2 | Khilan   | 2060 | 2008-05-20 00:00:00 | |  3 | kaushik |   3000 | 2009-10-08 00:00:00 |
| 3 | kaushik  | 1500 | 2009-10-08 00:00:00 | |  3 | kaushik |   1560 | 2009-11-20 00:00:00 |
| 3 | kaushik  | 2060 | 2008-05-20 00:00:00 | |  4 | Chaitali |   3000 | 2009-10-08 00:00:00 |
| 4 | Chaitali | 1500 | 2009-10-08 00:00:00 | |  4 | Chaitali |   1560 | 2009-11-20 00:00:00 |
| 4 | Chaitali | 2060 | 2008-05-20 00:00:00 | |  5 | Hardik |   3000 | 2009-10-08 00:00:00 |
| 5 | Hardik   | 1500 | 2009-10-08 00:00:00 | |  5 | Hardik |   1560 | 2009-11-20 00:00:00 |
| 5 | Hardik   | 2060 | 2008-05-20 00:00:00 | |  6 | Komal |   3000 | 2009-10-08 00:00:00 |
| 6 | Komal    | 1500 | 2009-10-08 00:00:00 | |  6 | Komal |   1560 | 2009-11-20 00:00:00 |
| 6 | Komal    | 2060 | 2008-05-20 00:00:00 | |  7 | Muffy |   3000 | 2009-10-08 00:00:00 |
| 7 | Muffy    | 1500 | 2009-10-08 00:00:00 | |  7 | Muffy |   1560 | 2009-11-20 00:00:00 |
| 7 | Muffy    | 2060 | 2008-05-20 00:00:00 | +----+----------+--------+---------------------+